ABSTRACT
Environmental mapping and robot navigation are the basis for realizing robot automation in modern agricultural production. This study proposes a new autonomous mapping and navigation method for gardening scene robots. First, a new LiDAR slam-based semantic mapping algorithm is proposed to enable the robots to analyze structural information from point cloud images and generate roadmaps from them. Secondly, a general robot navigation framework is proposed to enable the robot to generate the shortest global path according to the road map, and consider the local terrain information to find the optimal local path to achieve safe and efficient trajectory tracking; this method is equipped in apple orchards. The LiDAR was evaluated on a differential drive robotic platform. Experimental results show that this method can effectively process orchard environmental information. Compared with vnf and pointnet++, the semantic information extraction efficiency and time are greatly improved. The map feature extraction time can be reduced to 0.1681 s, and its MIoU is 0.812. The resulting global path planning achieved a 100% success rate, with an average run time of 4ms. At the same time, the local path planning algorithm can effectively generate safe and smooth trajectories to execute the global path, with an average running time of 36 ms.
ABSTRACT
Digital modelling stands as a pivotal step in the realm of Digital Twinning. The future trend of Digital Twinning involves automated exploration and environmental modelling in complex scenes. In our study, we propose an innovative solution for robot odometry, path planning, and exploration in unknown outdoor environments, with a focus on Digital modelling. The approach uses a minimum cost formulation with pseudo-randomly generated objectives, integrating multi-path planning and evaluation, with emphasis on full coverage of unknown maps based on feasible boundaries of interest. The approach allows for dynamic changes to expected targets and behaviours. The evaluation is conducted on a robotic platform with a lightweight 3D LiDAR sensor model. The robustness of different types of odometry is compared, and the impact of parameters on motion planning is explored. The consistency and efficiency of exploring completely unknown areas are assessed in both indoor and outdoor scenarios. The experiment shows that the method proposed in this article can complete autonomous exploration and environmental modelling tasks in complex indoor and outdoor scenes. Finally, the study concludes by summarizing the reasons for exploration failures and outlining future focuses in this domain.
ABSTRACT
[This corrects the article DOI: 10.3389/fpsyg.2022.839982.].
ABSTRACT
Over the past decade, neuroscience has been integrated into information systems as a new methodology and perspective to study and solve related problems. Therefore, NeuroIS has emerged as a new cutting-edge research field. This review aimed to identify, summarize, and classify existing NeuroIS publications through knowledge mapping and bibliometric analysis. To effectively understand the development trend of NeuroIS, this study referred to the journal selection index of the Association of Business Schools in 2021 and journals above three stars in the field of information management as the main selection basis. A total of 99 neuroscience papers and their citation data were included from 19 major information systems journals of SCI/SSCI. This study analyzed bibliometric data from 2010 to 2021 to identify the most productive countries, universities, authors, journals, and prolific publications in NeuroIS. To this end, VOSviewer was used to visualize mapping based on co-citation, bibliographic coupling, and co-occurrence. Keywords with strong citation bursts were also identified in this study. This signifies the evolution of this research field and may reveal potential research directions in the near future. In selecting research methods and analysis tools for NeuroIS, content analysis was used to further conclude and summarize the relevant trends. Moreover, a co-citation network analysis was conducted to help understand how the papers, journals, and authors in the field were connected and related, and to identify the seminal or pioneering major literature. For researchers, network maps visualized mainstream research and provided a structural understanding of NeuroIS. The review concludes by discussing potential research topics in this field.
ABSTRACT
Following the COVID-19 pandemic, online learning has become a new mode of learning that students must adapt to. However, the mechanisms by which students receive and grasp knowledge in the online learning mode remain unknown. Cognitive load theory (CLT) offers instructions to students considering the knowledge of human cognition. Therefore, this study considers the CLT to explore the internal mechanism of learning under the online mode in an experimental study. We recruited 76 undergraduates and randomly assigned them to four groups in which they will watch videos at four different kinds of speed (1.0× or 1.25× or 1.5× or 2× speed). The study observed and analyzed how video playback speed affected students' learning and cognitive load to obtain the following results: (1) Video playback speed significantly influenced the students' learning effect. The best effect was observed at the speed of 1.25× and 1.5×. (2) The speed that affected the learning effect best differed according to the students' learning abilities. High-level group students performed best at the speed of 1.5×, whereas low-level group students performed best at the speed of 1.25×. (3) The 1.5× speed showed significant differences in the learning effect by students' majors. This indicates that the cognitive load of liberal arts students increased greatly at this speed. (4) A change in playback speed has a significant impact on the cognitive load. Accelerated playback speed increases the cognitive load of students. The highest learning effect is observed under medium cognitive load.
ABSTRACT
Because of the coronavirus disease 2019 (COVID-19) pandemic, the traditional didactic teaching method that is practiced in Confucian culture, an Eastern cultural model, is being challenged by multiple alternative teaching modes. In Western cultures, the teaching behavior of teachers is dependent on their ability to influence the temperament of students; in contrast, teachers in Eastern cultures are influenced by changes in external environment (i.e., social policy). This phenomenon can mainly be explained by the tendency of students in Eastern cultures to adopt a passive learning style because of Confucianism. On the basis of Confucian culture and literature review, we conducted a Chinese-language questionnaire survey of temperament scales and learning motivation, and 724 effective questionnaires were collected and used to explore the relationship between students' temperament and learning motivation under three teaching modes, namely, online teaching, traditional offline classroom teaching, and online-offline mixed teaching. Conclusions drawn were as follows. (1) In a Chinese Confucian cultural system, the passive learning style of students and its relationship with the surrounding collective culture creates the temperament characteristics of sanguinity and phlegmatism. (2) Influenced by the traditional Confucian values of benevolence and honesty, students with a melancholic temperament do not focus on their learning motivations. Furthermore, changes in external information, to which such students are sensitive, cause them to give up opportunities easily. (3) Similarly, students with a choleric temperament are sensitive and prone to fluctuating emotions, and they tend to be affected by changes in their external environment. (4) Although students have a strong learning motivation under the traditional offline teaching mode, a paradox in individual cognition exists because of differences between Chinese and Western cultures. Therefore, students generally prefer the online-offline mixed teaching mode to the traditional single teaching mode. This study explored factors that influence students' learning motivation, namely, individual temperament and educational environment (e.g., teaching modes), and provides a reference for the future development of post epidemic education.
